2023-11-26 21:16:47 +04:00
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from sklearn.cluster import KMeans
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import pandas
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from matplotlib import pyplot as plt
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2023-11-26 22:54:55 +04:00
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factors = ['T', 'RH', 'D1', 'TI1', 'P']
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2023-11-26 21:16:47 +04:00
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kmeans = KMeans(n_clusters=4)
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data = pandas.read_csv('WindData.csv')
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i = 0
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for i in range(len(factors)):
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corr = data[['V1', factors[i]]]
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kmeans.fit(corr)
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plt.xlabel('V1', fontsize=14)
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plt.ylabel(factors[i], fontsize=14)
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plt.scatter(corr.values[:, 0], corr.values[:, 1], c=kmeans.labels_)
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plt.savefig('images/' + factors[i] + '-V1.png')
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plt.show()
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